The present invention relates to acoustic physiological monitoring and, more particularly, acoustic physiological monitoring during sleep.
Sleep monitoring systems often monitor snoring and apnea. Snoring and apnea are important indicia of sleep quality. Snoring is caused by the obstruction of respiratory airflow through the mouth and nose. Apnea is the cessation of respiratory airflow through the mouth and nose over a sustained period.
Snoring is characterized by rhythmic and loud breath sound. A snore segment in an acoustic physiological signal containing respiration sound may therefore be identified by detecting rhythm and loudness in the signal. Rhythm may be identified in the signal using various signal processing techniques, such as power spectrum density, autocorrelation or phase-locked loop techniques, whereas loudness in the signal may be gauged using various thresholding techniques.
Apnea is characterized by sustained absence of breath sound (i.e., at least ten seconds) interrupted by very loud breath sound (i.e., a snort or gasp as the person struggles to breathe). An apnea segment in an acoustic physiological signal containing respiration sound may therefore be identified by detecting sustained silence in the signal interrupted by a very loud sound in the signal.
Known sleep monitoring systems often suffer from a lack of adequate integration of snore and apnea detection. For example, some sleep monitoring systems do not use the loss of rhythm in an acoustic physiological signal after a snore segment as an indicator of the potential onset of apnea. Moreover, some sleep monitoring systems are ill-equipped to handle widely variant snoring rhythms exhibited by different people or the same person over time.